Decision Support System for Giving PDAM Tirtauli Pematangsiantar Employee Bonuses Using the Weighted Product (WP) Method

Penulis

  • Mira Ariffiani STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Irfan Sudahri Damanik STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Zulia Almaida Siregar STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

DOI:

https://doi.org/10.55123/jomlai.v2i1.346

Kata Kunci:

DSS, Employee Bonuses, PDAM Tirtauli, Weighted Product, Pematangsiantar

Abstrak

Employee Bonuses at PDAM Tirtauli Pematangsiantar are given to employees who are selected as employees of the workforce who perform their work in accordance with the profession through the selection process. The process of judgment and decision-making in selection is usually subjective when there are some recipients of employee bonuses who have not much different abilities. Applications created in this research in the form of Decision Support System Employee Bonus Employee PDAM Tirtauli Pematangsiantar Using Weighted Product Method. This application is used to assist the selection in conducting assessments of the competency of the recipients of employee bonus giving and recommendation in decision making. The assessment criteria used include other Attendance, Number of Children, Length of Work, Responsibility, and Loyalty. Weighted Product method is a method of completion by using multiplication to associate attribute values, where the value must be raised first with the attribute weights in question. The system is built using WEB and MySQL programming language for data processing. The result of the research is the application of the recipient of the employee bonus giving to facilitate the process of selecting the recipients of the employee bonus giving according to the need.

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Unduhan

Diterbitkan

2023-03-31

Cara Mengutip

Ariffiani, M., Damanik, I. S., & Siregar, Z. A. (2023). Decision Support System for Giving PDAM Tirtauli Pematangsiantar Employee Bonuses Using the Weighted Product (WP) Method. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 2(1), 69–74. https://doi.org/10.55123/jomlai.v2i1.346

Terbitan

Vol 2 No 1 (2023): March

Bagian

Articles

Lisensi

Hak Cipta (c) 2023 Mira Ariffiani, Irfan Sudahri Damanik, Zulia Almaida Siregar

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